Adaptive Machine Learning Algorithms with Python (PDF)
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Authors Chanchal Chatterjee and Vwani P. Roychowdhury begin by introducing a common framework for creating adaptive algorithms, and demonstrating how to use it to address various streaming data issues. Examples range from using matrix functions to solve machine learning and data analysis problems to more critical edge computation problems. They handle time-varying, non-stationary data with minimal compute, memory, latency, and bandwidth.
Upon finishing this book, you will have a solid understanding of how to solve adaptive machine learning and data analytics problems and be able to derive new algorithms for your own use cases. You will also come away with solutions to high volume time-varying data with high dimensionality in a low compute, low latency environment.
You will:
- Apply adaptive algorithms to practical applications and examples
- Understand the relevant data representation features and computational models for time-varying multi-dimensional data
- Derive adaptive algorithms for mean, median, covariance, eigenvectors (PCA) and generalized eigenvectors with experiments on real data
- Speed up your algorithms and put them to use on real-world stationary and non-stationary data
- Master the applications of adaptive algorithms on critical edge device computation applications
- Autor: Chanchal Chatterjee
- 2022, 1st ed, 269 Seiten, Englisch
- Verlag: APress
- ISBN-10: 1484280172
- ISBN-13: 9781484280171
- Erscheinungsdatum: 12.03.2022
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
- Dateiformat: PDF
- Grösse: 9.26 MB
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